Precision over quantity: identifying trustworthy genomic risk stratification models
Dear Editor, The Brazilian Society of Medical Genetics and Genomics recently issued a statement against using polygenic risk scores for breast cancer risk stratification in Brazilian women. In fact, an ongoing surge could be observed in genomic signatures and prognostic models, with over 200 LASSO-based TCGA signatures appearing in Scientific Reports last year, based on a focused keyword-based search, several of questionable quality. Discerning reliable models from unreliable ones is crucial for clinicians in order to avoid poorly validated tools. [...]
Authors
- Pedro Robson Costa Passos (ORCID: https://orcid.org/0009-0007-9049-0996)
- Valbert Oliveira Costa Filho (ORCID: https://orcid.org/0009-0003-2864-0966)
Institutions
- Universidade Federal do Ceará (BR)
Publication Details
- Journal
- Einstein (São Paulo)
- Published
- 2025-01-01
- DOI
- https://doi.org/10.31744/einstein_journal/2025ce1726
- Citations
- 3
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 7.44